LMX Cloud LLM Inference

quote_price

Estimate USDC cost for a single model call. Uses GET /v1/pricing with model and token params.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model": "<model>"
    },
    "name": "quote_price"
  }
}

Input Schema

Name	Required	Description
`model`	Yes	Model alias to quote (e.g. llama-3-70b).
`api_key`	No	Optional LMX API key (lmx_...). Prefer MCP client Authorization header or env; use this to override per call.
`max_tokens`	No	Optional max completion tokens for the quote.
`prompt_tokens`	No	Optional estimated prompt tokens (default: 1).

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 16, 2026

TDQS

A3.7/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description mentions GET method (read-only) but lacks details on auth, rate limits, error behavior, or side effects. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded with purpose, no fluff. Efficiently communicates core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks explanation of return value (estimated cost) and behavior in edge cases (e.g., rounding). No output schema. Adequate for a simple estimator but could be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all 4 parameters with descriptions (100% coverage). Description adds the context of 'Uses GET /v1/pricing' but no significant semantic enrichment beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'Estimate', resource 'USDC cost for a single model call', and distinguishes from siblings like get_pricing (pricing info) and chat_completion (executes call).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage (before model call) but no explicit when-to-use, when-not-to-use, or alternatives. Agent must infer context from sibling names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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